High prevalence of <i>Candida</i> species in the respiratory tract of patients diagnosed with SARS-CoV-2
Bibliographic record
Abstract
Coinfection and secondary infection by fungi in patients with viral pulmonary infection, especially SARS-CoV-2, are important factors that worsen the prognosis and are associated to increased death rates. This work aims to report the prevalence of Candida isolates in bronchoalveolar and nasopharyngeal samples from suspected COVID-19 patients in the first-second pandemic waves and their antifungal resistance profile. From 2321 patients, 29.04% were diagnosed with SARS-CoV-2 infection. The yeast isolation rate of 6.97% (47/674) from positive SARS-CoV-2 was statistically higher than 4.43% (73/1647) from negative SARS-CoV-2 patients ( p = 0.0177). Among yeasts, the most prevalent species was Candida albicans (63/120), with four being azole-resistant isolates (6.35%); however, other emerging and less susceptible species were also isolated, such as Candida guilliermondii (11), Candida glabrata (5), Candida lusitaniae (4), Candida krusei (1), and Candida norvegensis (1). Here, we highlighted Candida prevalence in respiratory tract, emphasizing the relevance for surveillance in SARS-CoV-2/COVID patients for improvement of management as well as patient outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".